Application of Back Propagation Neural Network for Partial Discharge Pattern Recognition

This paper proposes a pattern recognition approach based on the back propagation (BP) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). Pattern recognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, pattern recognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of model insulators with artificial defects are purposely created to produce the common PD activities of insulators by using feature vectors of field-test PD patterns. The experimental data are found to be in close agreement with the recognized data. The experimental results show that the proposed approach is very effective for recognizing the defects of high-voltage electrical apparatus.